World Models Will Soon Be Inescapable. Here’s What You Need to Know

The glow of a smartphone screen illuminating a New York City street corner at dusk—that’s the scene many remember from 2016, when millions of people chased virtual Pokémon across neighborhoods, captivated by the augmented reality of Pokémon Go. What those players didn't realize then is that the data generated by their interactions – the scans of sidewalks, buildings, and streetlights – are now foundational to a new generation of artificial intelligence: world models. These models, poised to reshape everything from robotics to driverless cars, represent a significant shift in how machines understand and interact with our physical world.

What Happened: The Rise of World Models

The initial spark for this technology can be traced back to the massive datasets collected by games like Pokémon Go. Niantic, the creator of Pokémon Go, recognized the value of this geographically rich data and has since pivoted to focus on building world models. This shift highlights a broader trend in the tech industry: leveraging entertainment and gaming to gather valuable data for AI development. The company’s current focus, Niantic Spatial, is dedicated to creating these digital twins of the real world, a process that requires immense computational power and sophisticated algorithms. The company’s decision to move away from game development and into AI underscores the growing recognition of world models as a transformative technology with far-reaching implications.

World models differ fundamentally from the large language models that have recently dominated headlines. While language models predict the next word in a sentence, world models use visual inputs to generate digital environments that simulate physics. Niantic, the creator of Pokémon Go, has pivoted heavily into this technology, leveraging its vast database of real-world locations to build increasingly sophisticated replicas. “We’re very much about reconstructing the real world,” explains Brian McClendon, Niantic Spatial’s chief technology officer. The potential applications are vast, and 2027 is projected to be a key year for the expansion of home robotics and autonomous vehicles, both of which rely on these advanced simulations.

The core function of a world model, according to Oliver Cameron, CEO of AI lab Odyssey, is to “predict the next visual state of the world” based on a given image. These digital environments serve as training grounds for robots and autonomous systems, allowing them to practice and refine their actions in a safe, simulated environment. McClendon describes a scenario where a robot's intended workspace is photographed, a 3D model is generated, and the software then runs “millions of simulations” to train the robot on the space’s parameters. This process eliminates the need for physical movement and allows for rapid iteration and improvement. The ability to simulate millions of scenarios allows for a level of training that would be impossible in the real world, significantly accelerating the development process and reducing the risk of costly errors.

Community Reaction: Data Collection and Labor in NYC

The development of world models isn’t solely confined to Silicon Valley giants. Companies like Wayve, which builds world models specifically for driverless cars, are utilizing dashcam footage to recreate hazardous road conditions for training purposes. Jamie Shotton, Wayve’s chief scientist, emphasizes the importance of understanding physics and cause-and-effect within these models, stating that they “must be able to react to the actions that we take in the world, and so it must understand physics, cause and effect, and how other objects and people change their actions in response to our own.” The implications extend beyond physical applications; even the video game industry, with major players like Tencent, are investing heavily in world model technology. This reflects a growing recognition that world models can enhance realism and create more immersive gaming experiences.

The rise of world models is also creating new, albeit often low-paying, opportunities for New Yorkers. To fuel the creation of these digital replicas, AI labs require vast amounts of real-world data. Earlier this year, one writer for *Wired* documented a growing trend: individuals recording videos of their daily routines—folding laundry, washing dishes—and selling that data through apps. While the financial rewards are currently modest, the demand for this type of data collection is likely to increase as more companies strive to build more comprehensive world models. This represents a subtle but significant shift in the labor market, where everyday activities are increasingly commodified for the benefit of artificial intelligence development. The ethical implications of this trend are complex, raising questions about data ownership, privacy, and the potential for exploitation. While some see it as a new form of gig work, others worry about the long-term consequences of turning everyday life into a source of data for AI companies. The low pay also highlights the economic disparities within the tech industry, where those creating the technology often benefit disproportionately from the labor of others.

Investment, Acquisition, and Future Developments

The financial commitment to world model technology is substantial. Yann LeCun, Meta’s former chief AI scientist, recently secured over a billion dollars to fund his startup, Advanced Machines Intelligence. Similarly, famed Stanford computer scientist Fei-Fei Li launched World Labs in 2024, which was subsequently acquired by AMD for over $8 billion. AMD’s acquisition of World Labs is particularly significant, as it signals a strategic move to integrate world model technology into its hardware and software offerings. These significant investments signal the widespread belief in the transformative potential of world models across various industries. Beyond investment, Niantic’s initial work with Pokémon Go’s data highlights the surprising origins of this technology. Looking ahead, we can expect to see increased collaboration between AI labs, hardware manufacturers, and data providers as the industry matures.

Katherine's Take: A Quiet Revolution and the Cost of Progress

The quiet revolution unfolding around world models is deeply significant for New Yorkers and communities across the nation. While we may not immediately notice these systems at work, they are quietly reshaping the future of transportation, manufacturing, and even entertainment. The reliance on data collected from everyday life raises important questions about privacy and the value of our personal routines. The fact that New Yorkers are now being asked to record videos of their chores for a small fee highlights a growing trend: the commodification of our lived experiences. It’s crucial that we, as a society, consider the ethical implications of this data collection and ensure that individuals are fairly compensated for their contributions. Beyond the economic considerations, there’s a broader question of how these simulations will impact our understanding of reality and the importance of genuine human interaction. The potential for these models to create increasingly realistic simulations also raises concerns about the blurring lines between the real and the virtual, and the need for critical thinking in a world saturated with AI-generated content.

Resources for Further Information

For those seeking a deeper understanding of world models and their applications, several resources are available. Niantic Spatial provides information on its approach to reconstructing the real world: Niantic Labs. Wayve offers insights into its work in autonomous driving, while Odyssey focuses on broader AI research. The websites of AMD and Tencent provide information on their respective investments in AI technology. Readers interested in the origins of the technology may find Reuters: Pokémon Go Creator Niantic Is Building World Models insightful, and those curious about Niantic’s current robotics efforts can learn more from Forbes: Niantic Is Using World Models to Bolster Its Autonomous Robotics Efforts.

As world models continue to evolve, it’s likely that their impact on our lives will only grow more profound. Understanding the underlying technology and its implications is essential for navigating the future and ensuring that these powerful tools are used responsibly and ethically, contributing to a society that values both technological progress and the enduring importance of human connection. The next few years will be critical in shaping the trajectory of world model development, and it is imperative that policymakers, researchers, and the public engage in informed discussions about the potential benefits and risks.